Botnet Attack Detection Approach in IoT Networks

被引：1

作者：

Tatarnikova, T. M. ^{[1
]}

Sikarev, I. A. ^{[3
]}

Bogdanov, P. Yu. ^{[2
]}

Timochkina, T. V. ^{[3
]}

机构：

[1] St Petersburg Electrotech Univ LETI, St Petersburg 197022, Russia

[2] St Petersburg State Univ Aerosp Instrumentat, St Petersburg 190000, Russia

[3] Russian State Hydrometeorol Univ, St Petersburg 195196, Russia

来源：

AUTOMATIC CONTROL AND COMPUTER SCIENCES | 2022年 / 56卷 / 08期

关键词：

Internet of things; network attack; intrusion detection system; autoencoder; principal component analysis; unsupervised learning;

D O I：

10.3103/S0146411622080259

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An approach to detecting network attacks based on deep learning (autoencoders) is proposed. It is shown that learning examples can be obtained by connecting IoT devices to the network, as long as the traffic does not carry malicious code. Statistical values and functions extracted from traffic are proposed; patterns of IoT devices are based on them.

引用

页码：838 / 846

页数：9

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